1. Field of Invention
This application relates, in general, deep brain stimulation targeting based on brain connectivity and more particularly to methods of use.
2. Description of Related Art
The efficacy of deep brain stimulation (DBS) critically depends on accurate and precise targeting of subcortical targets. The lack of preoperative methods to either structurally or functionally delineate thalamic nuclear anatomy usually necessitates indirect targeting of the thalamus based on atlas-derived coordinates. Although indirect targeting of the thalamus is generally robust, variability in cortical and subcortical anatomy and function across individuals and across disease states would suggest that methods to identify patient-specific targets within the thalamus (or any other subcortical target) could enhance the safety and efficacy of DBS surgery.
The variability in anatomy and function of subcortical nuclei has been reported extensively in the functional neurosurgery and basic science literature. When targeting relative to the anterior and posterior commisures (AC and PC, respectively), efficacious targets for DBS are at best represented by a probability cloud of optimal electrode placement. Preoperative identification of a precise anatomical or physiological target is even more complicated in the thalamus where there are no readily visible nuclear boundaries that provide patient-specific details to guide targeting. Imaging and analysis techniques that can segment die thalamic nuclei can therefore aid in identifying patient-specific targets for DBS.
Prior studies have reported unique strategies for thalamic segmentation, including using spontaneous contrast and microscopic voxels in high-field magnetic resonance imaging (MRI) and using diffusion tensor magnetic resonance imaging (DTI) to evaluate characteristic fiber orientation of corticothalamic/thalamocortical striations within each thalamic nucleus. While these techniques are valid, their utility or reliability with respect to DBS targeting has not been evaluated. Moreover, in some cases, implementation of the described methodologies requires expertise and resources (e.g., 4.7 T MRI) that are not conventionally available to most physicians.
Based on the rationale that DBS likely exerts its efficacy by modulating activity at the network level, the present invention provides for connectivity-based segmentation of thalamic nuclei as a reliable and robust methodology for identifying optimal patient-specific targets for DBS electrode implantation. The importance of connectivity in mediating DBS efficacy was recently highlighted by optogenetic studies that implemented cortico-subthalamic projection fibers in the mechanism of efficacy of DBS of the subthalamic nucleus for Parkinson's disease. For example, it has been reported that using probabilistic diffusion tractography to identify thalamic subregions (i.e., nuclei) with unique patterns of cortical connectivity that were analogous to those previously described in histological and non-human primate studies and that were reproducible between individuals. Other reports have since provided functional-anatomic validation of thalamic segmentation using this approach and confirmed the reproducibility of the results. Such methodology has subsequently been used to segment other cortical, and deep brain targets, including but not limited to the substantia nigra, the subgenual cingulate, and the parietal cortex. Despite its increased application in the basic sciences, the value of using connectivity-based thalamic segmentation to guide DBS implantation has not been extensively evaluated.
In light of the foregoing, it would therefore be useful to provide a means of improving the precision of DBS targeting, in which connectivity-based analyses also can provide insight into the mechanisms and networks mediating DBS efficacy and overcome the above and other disadvantages of known methodologies. It would be useful to analyse optimal thalamic DBS electrode locations for tremor control in relation to patterns of connectivity-based thalamic segmentation in order to evaluate a patient-specific means of targeting DBS electrodes. It would be useful to conduct DTI-based analyses using available and easy-to-use image analysis software. And it would be useful to compare the variability of targeting relative to DTI-based maps to that seen with AC-PC reference frame and describe the variability in targeting across patients.